BackgroundArtemisinin combination therapy (ACT) is recommended as first-line treatment for uncomplicated Plasmodium falciparum malaria, whereas chloroquine is still commonly used for the treatment of non-falciparum species (Plasmodium vivax, Plasmodium ovale and Plasmodium malariae). A more simplified, more uniform treatment approach across all malaria species is worthwhile to be considered both in endemic areas and for malaria as an imported condition alike.MethodsA PROSPERO-registered systematic review to determine the efficacy and safety of ACT for the treatment of non-falciparum malaria was conducted, following PRISMA guidelines. Without language restrictions, Medline/PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, LILACS, Biosis Previews and the African Index Medicus were searched for studies published up to November 2014.ResultsThe literature search identified 986 reports; 40 publications were found eligible for inclusion, all of them on non-falciparum malaria in endemic areas. Most evidence was available for P. vivax (n = 35). Five clinical trials in total were identified evaluating ACT for P. ovale, P. malariae and Plasmodium knowlesi. Most ACT presentations have high efficacy against P. vivax parasites; artemisinin-based combinations have shorter parasite and fever clearance times compared to chloroquine. ACT is as effective as chloroquine in preventing recurrent parasitaemia before day 28. Artemisinin-based combinations with long half-lives show significantly fewer recurrent parasitaemia up to day 63. The limited evidence available supports both the use of chloroquine and an ACT for P. ovale and P. malariae. ACT seems to be preferable for optimal treatment of P. knowlesi.ConclusionACT is at least equivalent to chloroquine in effectively treating non-falciparum malaria. These findings may facilitate development of simplified protocols for treating all forms of malaria with ACT, including returning travellers. Obtaining comprehensive efficacy and safety data on ACT use for non-falciparum species particularly for P. ovale, P. malariae and P. knowlesi should be a research priority.Trial registrationCRD42014009103Electronic supplementary materialThe online version of this article (doi:10.1186/1475-2875-13-463) contains supplementary material, which is available to authorized users.
BackgroundRecent studies alluded to the alarming scale of poor anti-malarial drug quality in malaria-endemic countries, but also illustrated the major geographical gaps in data on anti-malarial drug quality from endemic countries. Data are particularly scarce from Central Africa, although it carries the highest burden of malaria. The aim of this medicine quality field survey was to determine the prevalence of poor-quality anti-malarial drugs in Gabon.MethodsA field survey of the quality of anti-malarial drugs in Gabonese pharmacies was conducted using the Global Pharma Health Fund Minilab® tests, following the Medicine Quality Assessment Reporting Guidelines. Anti-malarial drugs were purchased randomly from selected pharmacies in Gabon. Semi-quantitative thin-layer chromatography (TLC) and disintegration testing were carried out to measure the concentration of active pharmaceutical ingredients (APIs). The samples failing the TLC test were analysed by high-performance liquid chromatography. Following the collection of anti-malarial drugs, a street survey was conducted to understand where people purchase their anti-malarial drugs.ResultsA total of 432 samples were purchased from 41 pharmacies in 11 cities/towns in Gabon. The prevalence of poor-quality anti-malarial drugs was 0.5% (95% CI 0.08–1.84%). Two out of 432 samples failed the MiniLab® semi-quantitative TLC test, of which a suspected artemether-lumefantrine (AL) sample was classified as falsified and one sulfadoxine-pyrimethamine (SP) sample as substandard. High performance liquid chromatography with ultraviolet photo diode array detection analysis confirmed the absence of APIs in the AL sample, and showed that the SP sample did contain the stated APIs but the amount was half the stated dose. Of the people interviewed, 92% (187/203) purchased their anti-malarial drugs at a pharmacy.ConclusionUsing the GPHF Minilab®, the prevalence of poor-quality anti-malarial drugs is far lower than anticipated. The findings emphasize the need for randomized and robust sampling methods in order to collect representative data on anti-malarial drug quality.Trial registration: NTR4341 (Dutch Trial Registry)Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-015-0795-z) contains supplementary material, which is available to authorized users.
BackgroundThere is a need for accurate and field-applicable instruments for the evaluation of the quality of anti-malarial drugs. The aim of this study was to determine the diagnostic accuracy of the NanoRam®, a handheld Raman spectrometer (RS), to identify anti-malarial drugs.MethodsIn total, 289 anti-malarial drugs collected in a randomized field survey in Gabon were evaluated. The samples were compared with authentic products as supplied by the official manufacturer. To determine the sensitivity and specificity of the handheld NanoRam® spectrometer in the identification of anti-malarial drugs, a two-gate reversed-flow design was applied. The standards for reporting of diagnostic accuracy studies (STARD) were followed. The index test was the handheld RS. The reference test standards were thin layer chromatography and high performance liquid chromatography with ultraviolet photo diode array detection.ResultsThe sensitivity [95 % confidence interval (95 % CI)] and specificity of the RS to correctly identify an anti-malarial drug were 100 % (95 % CI 94.9–100 %) and 96 % (95 % CI 92.3–99.0 %), respectively. The RS could not differentiate between different batches of the same product or different manufacturers of the same product. Intra-observer agreement for 289 samples was 100 %. The average time to conduct the RS was 15 s per sample compared to 45 min per sample for TLC.ConclusionThe handheld RS holds promise as an easy-to-use, quick and field-applicable instrument for the evaluation of quality of anti-malarial drugs, potentially empowering pharmacists, drug inspectors and medical regulatory authorities.Trial registration NTR4341 (Dutch Trial Registry)Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-016-1212-y) contains supplementary material, which is available to authorized users.
Abstract. The serum lipid profile in malaria patients has been found to differ from that of healthy controls. We investigated serum lipid profile changes in malaria patients over time compared with patients with other febrile diseases. In total, 217 patients were included in the study (111 malaria patients and 106 symptomatic controls, defined as malaria-negative febrile patients). Serum lipid levels (mmol/L) were significantly lower in malaria patients compared with those with other febrile diseases (total cholesterol . No significant differences were found for apolipoprotein A1, apolipoprotein B, and lipoprotein(a). Cholesterol levels increased toward reference values on day 28 ( TC = 3.26-3.98, P < 0.001; HDL-C = 0.43-0.96, P < 0.001; LDL-C = 2.05-2.60, P < 0.001). TG levels decreased from 1.81 on admission to 1.76 (day 3) and 0.88 (day 28; P = 0.130). Lipid profile changes were not correlated with parasitemia or Plasmodium falciparum histidine-rich protein 2 levels. This study confirms characteristic temporary lipid profile changes in malaria. Lipid profile changes demonstrated a good accuracy to discriminate between malaria and other febrile diseases (area under the curve = 0.80 (95% confidence interval = 0.742-0.863, P < 0.001). Several plausible hypotheses exist regarding the pathophysiology of lipid profile changes in malaria. Further studies to elucidate the precise pathways may lead to improved understanding of the underlying pathophysiology.[
Objective Inappropriate prescribing of drugs is associated with unnecessary harms for patients and healthcare costs. Interventions to reduce these prescriptions are widely studied, yet the effectiveness of different types of interventions remains unclear. Therefore, we provide an overview regarding the effectiveness of intervention types that aim to reduce inappropriate drug prescriptions, unrestricted by target drugs, population or setting. Methods For this overview, systematic reviews (SRs) were used as the source for original studies. EMBASE and MEDLINE were searched from inception to August 2018. All SRs aiming to evaluate the effectiveness of interventions to reduce inappropriate prescribing of drugs were eligible for inclusion. The SRs and their original studies were screened for eligibility. Interventions of the original studies were categorized by type of intervention. The percentage of interventions showing a significant reduction of inappropriate prescribing were reported per intervention category. Key findings Thirty-two SRs were included, which provided 319 unique interventions. Overall, 61.4% of these interventions showed a significant reduction in inappropriate prescribing of drugs. Strategies that were most frequently effective in reducing inappropriate prescribing were multifaceted interventions (73.2%), followed by interventions containing additional diagnostic tests (antibiotics) (70.4%), computer interventions (69.2%), audit and feedback (66.7%), patient-mediated interventions (62.5%) and multidisciplinary (team) approach (57.1%). The least frequently effective intervention was an education for healthcare professionals (50.0%). Conclusion The majority of the interventions were effective in reducing inappropriate prescribing of drugs. Multifaceted interventions most frequently showed a significant reduction of inappropriate prescribing. Education for healthcare professionals is the most frequently included intervention in this overview, yet this category is least frequently effective.
ObjectiveWe aimed to increase the understanding of the scaling of de-implementation strategies by identifying the determinants of the process and developing a determinant framework.Design and methodsThis study has a mixed-methods design. First, we performed an integrative review to build a literature-based framework describing the determinants of the scaling of healthcare innovations and interventions. PubMed and EMBASE were searched for relevant studies from 1995 to December 2020. We systematically extracted the determinants of the scaling of interventions and developed a literature-based framework. Subsequently, this framework was discussed in four focus groups with national and international de-implementation experts. The literature-based framework was complemented by the findings of the focus group meetings and adapted for the scaling of de-implementation strategies.ResultsThe literature search resulted in 42 articles that discussed the determinants of the scaling of innovations and interventions. No articles described determinants specifically for de-implementation strategies. During the focus groups, all participants agreed on the relevance of the extracted determinants for the scaling of de-implementation strategies. The experts emphasised that while the determinants are relevant for various countries, the implications differ due to different contexts, cultures and histories. The analyses of the focus groups resulted in additional topics and determinants, namely, medical training, professional networks, interests of stakeholders, clinical guidelines and patients’ perspectives. The results of the focus group meetings were combined with the literature framework, which together formed the supporting the scaling of de-implementation strategies (SPREAD) framework. The SPREAD framework includes determinants from four domains: (1) scaling plan, (2) external context, (3) de-implementation strategy and (4) adopters.ConclusionsThe SPREAD framework describes the determinants of the scaling of de-implementation strategies. These determinants are potential targets for various parties to facilitate the scaling of de-implementation strategies. Future research should validate these determinants of the scaling of de-implementation strategies.
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